Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It lists capabilities but does not disclose whether the operation mutates state, how speaker_id or world_state affect behavior, what failure looks like, or any constraints on input.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The entire description is one front-loaded sentence with concrete examples and no filler. It is easy to scan and every phrase adds meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations, 0% parameter coverage, and many similar cognitive.* siblings, the description needs to provide selection cues and input semantics. It only covers high-level intent resolution; the output schema covers return values, but the rest remains incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description never mentions utterance, speaker_id, or world_state. It adds no parameter-level meaning and does not compensate for the missing schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific domain (Pragmatics) and three concrete tasks: resolving indirect speech acts, anaphoric pronouns, and verifying presuppositions. This is specific enough to distinguish the tool from siblings like cognitive.parse_task or cognitive.ground_language.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool—when an utterance involves non-literal meaning, anaphora, or presuppositions—but it gives no explicit guidance versus cognitive.parse_task, cognitive.analyze_communication, or cognitive.ground_language. No exclusions or alternative routing are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.